Assessment of urban flood risk based on data-driven models: A case study in Fuzhou City, China

大洪水 洪水(心理学) 洪水风险评估 环境科学 危害 水资源管理 脆弱性(计算) 中国 水文学(农业) 地理 风险评估 百年一遇洪水 风险分析(工程) 地质学 计算机科学 岩土工程 医学 考古 心理学 化学 计算机安全 有机化学 心理治疗师
作者
Chenlei Ye,Zongxue Xu,Xiaohui Lei,Weihong Liao,Xingchen Ding,Yongshuai Liang
出处
期刊:International journal of disaster risk reduction [Elsevier]
卷期号:82: 103318-103318 被引量:10
标识
DOI:10.1016/j.ijdrr.2022.103318
摘要

In response to the growing threat of urban flooding, this study developed an integrated method to evaluate the flood risk of the study area (Fuzhou City, China) to different types of urban flooding. First, a coupled hydrological–hydrodynamic model was developed to obtain the key dynamic flood factors forced by typical rainstorm events with river levee overtopping and pipeline transportation. Second, an integrated framework was developed to assess urban flood vulnerability under different flood hazard scenarios. Fifteen features were selected and their relative importance was analyzed by using the XGBoost model. Finally, a cloud model was used to realize qualitative to quantitative characterization of subregions of urban flood risk. The results highlighted the flooding nodes, and the inundation areas presented increasing trends with the increase of return periods. The inundation degree was divided into four categories based on the inundation degree, for which the flooding area was 324.30, 177.81, 43.42, and 20.93 ha, respectively. Six explanatory variables with greater importance were recognized in all schemes. The risk level of subregions changed dynamically, when the rainfall intensity increased, the risk level of subregions showed an increasing trend. Areas with intermediate and high risk were concentrated in the central and western of the study area. At the drainage subregion scale, two types of subareas are essential in urban flood management, respectively, the subregions with high risk in specific rainfall, and the subregions easily transforming into high-risk areas when rainfall increases. This study provides promising references in urban flood risk management.
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